Scatter plot of the feature vector using the complete dataset: Class 0 (normal, blue dots), Class 1 (COVID-19, red dots), Class 2 (viral pneumonia, purple dots), and Class 3 (lung opacity, yellow dots). (a) Without the tuning weight parameter <i>ω</i>. (d) With the tuning weight parameter <i>ω</i>. The plots have similar shapes but exhibit a drift that aids in differentiating classes.

مواد مشابهة

• Partial dependency plots of singular values during testing, with and without the tuning weight <i>ω</i>: Class 0 (normal, blue dots), class 1 (COVID-19, red dots), class 2 (viral pneumonia, purple dots), and class 3 (lung opacity, yellow dots).
  حسب: Antonio Quintero-Rincón (21087716)
  منشور في: (2025)
• Partial dependency plots of conditional indices during testing, with and without the tuning weight <i>ω</i>: Class 0 (normal, blue dots), Class 1 (COVID-19, red dots), Class 2 (viral pneumonia, purple dots), and Class 3 (lung opacity, yellow dots).
  حسب: Antonio Quintero-Rincón (21087716)
  منشور في: (2025)
• Fit of the non-parametric empirical distribution to the variance-covariance matrix data: Class 0 (normal, blue dots), Class 1 (COVID-19, red dots), Class 2 (viral pneumonia, purple dots), and Class 3 (lung opacity, yellow dots).
  حسب: Antonio Quintero-Rincón (21087716)
  منشور في: (2025)
• Thresholds for all data with and without the tuning weight parameter (<i>ω</i>). Feature values for SVD (<i>ζ</i>) and the conditional index (<i>η</i>) are different and can serve with a threshold detection scheme.
  حسب: Antonio Quintero-Rincón (21087716)
  منشور في: (2025)
• Statistics of the smoothing parameter <i>h</i> across all images and classes.
  حسب: Antonio Quintero-Rincón (21087716)
  منشور في: (2025)